Method and Device for Balancing Foreground-Background Luminosity

ABSTRACT

In one embodiment, a method includes: obtaining a first image of a scene while an illumination component is set to an inactive state; obtaining a second image of the scene while the illumination component is set to a pre-flash state; determining one or more illumination control parameters for the illumination component for a third image of the scene that satisfy a foreground-background balance criterion based on a function of the first and second images in order to discriminate foreground data from background data within the scene; and obtaining the third image of the scene while the illumination component is set to an active state in accordance with the one or more illumination control parameters.

RELATED APPLICATION

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/514,544, filed on Jun. 2, 2017, entitled “Method and Device forBalancing Foreground-Background Luminosity,” the entire contents ofwhich are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates generally to image processing, and inparticular, to balancing the foreground-background luminosity of flashphotography.

BACKGROUND

When an image is captured using flash, the resulting image oftenincludes bothersome by-products, such as hot shadows, red-eye, andover-exposed areas, due to imbalanced foreground-background luminosity.These issues are further exacerbated when using smartphone cameras withconstrained flash and/or image sensor components.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the present disclosure can be understood by those of ordinaryskill in the art, a more detailed description may be had by reference toaspects of some illustrative embodiments, some of which are shown in theaccompanying drawings.

FIG. 1 illustrates a block diagram of an electronic device in accordancewith some embodiments.

FIG. 2 illustrates a block diagram of an image capture architecture ofthe electronic device in FIG. 1 in accordance with some embodiments.

FIG. 3 illustrates an image capture environment in accordance with someembodiments.

FIG. 4 illustrates a flowchart representation of a method of balancingforeground-background luminosity in accordance with some embodiments.

FIG. 5 illustrates a flowchart representation of a method of balancingforeground-background luminosity in accordance with some embodiments.

FIG. 6 illustrates image processing and analysis steps of the methods inFIGS. 4-5 in accordance with some embodiments.

FIG. 7 illustrates images associated with the image processing andanalysis steps of the methods in FIGS. 4-5 in accordance with someembodiments.

FIG. 8 illustrates example graphical representations of a flash durationrelative to an image exposure window in accordance with someembodiments.

FIG. 9 is a block diagram of a computing device in accordance with someembodiments.

In accordance with common practice, various features shown in thedrawings may not be drawn to scale, as the dimensions of variousfeatures may be arbitrarily expanded or reduced for clarity. Moreover,the drawings may not depict all of the aspects and/or variants of agiven system, method or apparatus admitted by the specification.Finally, like reference numerals are used to denote like featuresthroughout the figures.

DESCRIPTION OF EXAMPLE EMBODIMENTS

FIG. 1 is a block diagram of an electronic device 100 in accordance withsome embodiments. While pertinent features are shown, those of ordinaryskill in the art will appreciate from the present disclosure thatvarious other features have not been illustrated for the sake of brevityand so as not to obscure more pertinent aspects of the exampleembodiments disclosed herein. To that end, as a non-limiting example,the electronic device 100 includes: one or more processors 102 (e.g.,microprocessors, central processing units (CPUs), graphical processingunits (GPUs), application-specific integrated circuits (ASICs),field-programmable gate arrays (FPGAs), and/or the like), a power source104 (e.g., a capacitance storage device, a battery, and/or circuitry fordrawing power from an external alternating current (AC) and/or directcurrent (DC) source), a bus 105 for interconnecting the elements of theelectronic device 100, and non-transitory memory 106. In someembodiments, the non-transitory memory 106 includes random-access memorysuch as dynamic random-access memory (DRAM), static random-access memory(SRAM), double data rate random-access memory (DDR RAM), and/or otherrandom-access solid-state memory devices. In some embodiments, thenon-transitory memory 106 includes non-volatile memory such as one ormore magnetic disk storage devices, one or more optical disk storagedevices, one or more flash memory devices, and/or one or more othernon-volatile solid-state storage devices.

In some embodiments, the electronic device 100 also includes: one ormore input/output (I/O) devices 110 (e.g., a touch screen display, atouchpad, a mouse, a keyboard, microphone(s), speaker(s), physicalbutton(s), and/or the like), an optional display 112, and one or morenetwork interfaces 114. In some embodiments, the one or more networkinterfaces 114 include, for example, interfaces and circuitry for apersonal area network (PAN), such as a BLUETOOTH network, for a localarea network (LAN), such as an 802.11x Wi-Fi network, and/or for a widearea network (WAN), such as a 4G cellular network.

In some embodiments, the electronic device 100 further includes: animage capture component 120 and an illumination component 130. In someembodiments, the image capture component 120 includes an image sensor122 and an optional lens assembly 124. In some embodiments, the imagecapture component 120 also optionally includes a shutter, aperture,and/or the like for capturing image data (sometimes also referred toherein as “images”). For example, the image sensor 122 corresponds to acharge-coupled device (CCD) image sensor. In another example, the imagesensor 122 corresponds to a complementary metal-oxide semiconductor(CMOS) image sensor. For example, the illumination component 130corresponds to a flash, strobe, or other suitable light source such asone or more light emitting diodes (LEDs), one or more xenon bulbs,and/or the like. In some embodiments, the illumination component 130 isseparate from the electronic device 100 and is controlled by theelectronic device 100 via the one or more network interfaces 114 (e.g.,an off-camera flash/strobe).

In some embodiments, the electronic device 100 corresponds to a portablecomputing device such as a digital camera, a smartphone, a tablet, alaptop computer, a wearable computing device, and/or the like. In someembodiments, the electronic device 100 corresponds to a computing devicesuch as a set-top box (STB), over-the-top (OTT) box, gaming console,desktop computer, kiosk, and/or the like.

The various functional blocks shown in FIG. 1 may include hardwareelements (including circuitry), software elements (including computercode stored on a computer-readable medium), or a suitable combination ofhardware and software elements. It should further be noted that FIG. 1is merely one example of a particular implementation and is intended toillustrate non-limiting components that may be present in the electronicdevice 100.

FIG. 2 is a block diagram of an image capture architecture 200 of theelectronic device 100 in accordance with some embodiments. Whilepertinent features are shown, those of ordinary skill in the art willappreciate from the present disclosure that various other features havenot been illustrated for the sake of brevity and so as not to obscuremore pertinent aspects of the example embodiments disclosed herein. Forexample, in some embodiments, the image capture architecture 200 issimilar to and adapted from the electronic device 100 in FIG. 1. Assuch, FIG. 1 and FIG. 2 include similar elements labeled with the samereference number in both figures have the same function, with only thedifferences described herein for the sake of brevity.

To that end, as a non-limiting example, the image capture architecture200 includes an image capture control module 210, an image processingmodule 220, and an image analysis module 230. According to variousembodiments, the modules 210, 220, and 230 may include hardware elements(including circuitry), software elements (including computer code storedon a computer-readable medium), or a suitable combination of hardwareand software elements. For example, the modules 210, 220, and 230correspond to software modules (e.g., programs, computer code,instructions, and/or the like) executed by the one or more processors102.

In some embodiments, the image capture control module 210 is configuredto control the functions of the image capture component 120 and theillumination component 130 based on image analysis data obtained fromthe image analysis module 230 and/or inputs/requests obtained from theone or more I/O devices 110 (e.g., an image capture input/request).According to some embodiments, the image capture control module 210instructs the image capture component 120 to capture image data(sometimes also referred to herein as “images”) in accordance with oneor more image parameters such as specified values for gain, exposure,aperture, shutter speed, ISO, and/or the like. In some embodiments, theimage capture control module 210 instructs the image capture component120 to capture image data according to known auto-focus (AF),auto-exposure (AE), auto-white balance (AWB), and/or optical imagestabilization (OSI) algorithms or techniques in the art.

According to some embodiments, the image capture control module 210instructs the illumination component 130 to function in accordance withone of an active state, a pre-flash state, or an inactive state. In someembodiments, the image capture control module 210 instructs theillumination component 130 to function in the active state based on oneor more illumination controls parameters such as duration, timingrelative to the image exposure window, intensity, color temperature,directionality, and/or the like.

In some embodiments, the image processing module 220 is configured toobtain raw image data from the image capture component 120 (e.g., fromthe image sensor 122). In some embodiments, the image processing module220 is also configured to pre-processes the raw image data to producepre-processed image data. In various embodiments, the pre-processingincludes, for example, converting a RAW image into an RGB or YCbCrimage. In various embodiments, the pre-processing further includes gainadjustment, color enhancement, denoising, filtering, and/or the like. Insome embodiments, the image processing module 220 is further configuredto provide the raw image data and/or the pre-processed image data to thedisplay 112 for rendering thereon. In some embodiments, the imageprocessing module 220 is further configured to provide the raw imagedata and/or the pre-processed image data to the non-transitory memory106 for storage therein.

In some embodiments, the image analysis module 230 is configured toobtain the raw image data and/or the pre-processed image data from theimage processing module 220 and perform image analysis thereon. In someembodiments, the image analysis module 230 is also configured todetermine one or more image parameters and/or one or more illuminationcontrol parameters based on the image analysis, which is, in turn,provided to the image capture control module 210. In some embodiments,the image analysis module 230 is further configured to provide the imageanalysis data to the non-transitory memory 106 for storage therein.

The various functional blocks shown in FIG. 2 may include hardwareelements (including circuitry), software elements (including computercode stored on a computer-readable medium), or a suitable combination ofhardware and software elements. It should further be noted that FIG. 2is merely one example of a particular implementation and is intended toillustrate non-limiting components that may be present in the imagecapture architecture 200.

FIG. 4 is a flowchart representation of a method 400 of capturing animage with balanced foreground-background luminosity in accordance withsome embodiments. In some embodiments (and as detailed below as anexample), the method 400 is performed by an electronic device (or aportion thereof) such as the electronic device 100 in FIG. 1 or theimage capture architecture 200 in FIG. 2, that includes one or moreprocessors, non-transitory memory, an image sensor, and an illuminationcomponent. For example, the electronic device includes an image capturearchitecture with a suitable combination of an image sensor, lensassembly, shutter, aperture, and/or the like. For example, theillumination component corresponds to a flash/strobe including one ormore LEDs.

In some embodiments, the method 400 is performed by processing logic,including hardware, firmware, software, or a suitable combinationthereof. In some embodiments, the method 400 is performed by one or moreprocessors executing code, programs, or instructions stored in anon-transitory computer-readable storage medium (e.g., a non-transitorymemory). Some operations in method 400 are, optionally, combined and/orthe order of some operations is, optionally, changed. Briefly, themethod 400 includes determining illumination control parameters and/orimage parameters based on analysis of a first ambient image and a secondpre-flash image in order to capture an image with balancedforeground-background luminosity.

The method 400 begins, at block 402, with the electronic deviceobtaining (e.g., capturing) a first ambient image of a scene. Forexample, with reference to FIG. 2, while the illumination component 130is set to the inactive state, the image capture architecture 200 obtainsthe first image data (e.g., RAW image data) of the scene from the imagesensor 122. As one example, FIG. 3 illustrates an image captureenvironment 300 in accordance with some embodiments. As shown in FIG. 3,the display 112 (e.g., the view finder) of the electronic device 100shows a preview of the scene 310. For example, the image capturecomponent 120 (e.g., a rear facing camera) of the electronic device 100captures an image of the scene 310 while the illumination component 130is set to the inactive state. According to some embodiments, the firstambient image is captured while the image capture architecture 200operates the image capture component 120 according to known AF, AE, AWB,and/or OSI algorithms or techniques in the art.

The method 400 continues, at block 404, with the electronic deviceobtaining (e.g., capturing) a second pre-flash image of the scene. Forexample, with reference to FIG. 2, while the illumination component 130is set to the pre-flash state (e.g., the flash/strobe is set to a torchor flashlight mode with a predetermined intensity value of Q % such at75%), the image capture architecture 200 obtains the second image data(e.g., RAW image data) of the scene from the image sensor 122. Accordingto some embodiments, the second pre-flash image is captured while theimage capture architecture 200 operates the image capture component 120according to known AF, AE, AWB, and/or OSI algorithms or techniques inthe art.

According to some embodiments, the first ambient image is captured priorto the second pre-flash image. In some embodiments, when the firstambient image is captured prior to the second pre-flash image, one ormore subsequent ambient images are captured to provide further iterativedata points for the analysis at block 406. According to someembodiments, the first ambient image is captured after the secondpre-flash image. In some embodiments, the first ambient image and thesecond pre-flash image are captured within a predefined time period ofone another (e.g., within 100 ns, 100 μs, 1 ms, 10 ms, etc.).

The method 400 continues, at block 406, with the electronic deviceanalyzing the first and second images in order to discriminateforeground data from background data in the scene. In some embodiments,the one or more illumination parameters are set based on the first andsecond images such that a foreground-background balance criterion issatisfied in order to discriminate foreground data from background datain the scene. For example, with reference to FIG. 2, the imageprocessing module 220 pre-processes the first image data and the secondimage data. Continuing with this example, with reference to FIG. 2, theimage analysis module 230 performs image analysis on the pre-processedfirst image data and second image data (or a comparison/functionthereof) to obtain image analysis data (e.g., the analysis results).

In some embodiments, the analysis of the first and second imagescorresponds to the difference equation. In some embodiments, theanalysis of the first and second images corresponds to a luminancedifference. In some embodiments, the analysis of the first and secondimages corresponds to a relative difference with respect to brightness.In some embodiments, the analysis of the first and second imagescorresponds to a soft decision.

According to some embodiments, with reference to FIG. 2 and FIG. 6, theimage processing module 220 obtains an ambient RAW image 610 a (e.g.,the first image captured while the illumination components 130 is set tothe inactive state) from the image sensor 122. Continuing with thisexample, the image processing module 220 performs image processing onthe ambient RAW image 610 a to convert the ambient RAW image 610 a to anambient JPG image 610 b (e.g., the pre-processed first image).Thereafter, the image analysis module 230 performs image analysis on theambient JPG image 610 b. For example, with reference to FIG. 2 and FIG.6, the image analysis module 230 generates a luminosity histogram 615based on the ambient JPG image 610 b.

Similarly, according to some embodiments, with reference to FIG. 2 andFIG. 6, the image processing module 220 obtains a pre-flash RAW image620 a (e.g., the second image captured while the illumination components130 is set to the pre-flash state) from the image sensor 122. Continuingwith this example, the image processing module 220 performs imageprocessing on the pre-flash RAW image 620 a to convert the pre-flash RAWimage 620 a to a pre-flash JPG image 620 b (e.g., the pre-processedsecond image). Thereafter, the image analysis module 230 performs imageanalysis on the pre-flash JPG image 620 b. For example, with referenceto FIG. 2 and FIG. 6, the image analysis module 230 generates aluminosity histogram 625 based on the pre-flash JPG image 620 b.

In some embodiments, the image analysis module 230 generates theluminosity histogram using known algorithms or techniques in the art.According to some embodiments, the luminosity histogram is a statisticalrepresentation of pixel luminous levels within the image. For example,the left edge of the luminosity histogram indicates a number of pixelswithin the image that are pure black. Furthermore, in this example, theright edge of the luminosity histogram indicates a number of pixels thatare pure white. In other words, the luminosity histogram indicates theperceived brightness distribution or “luminosity” within the image.

According to some embodiments, with reference to FIG. 2 and FIG. 6, theimage analysis module 230 determines an amount of light to add to thescene for a third primary image based on the luminosity histogram 625 inorder to balance the foreground-background luminosity. In turn, theimage analysis module 230 (or the image capture control module 210)determines one or more illumination control parameters (e.g., the flashduration, intensity, timing relative to the image exposure window, colortemperature, directionality, and/or the like) for the third primaryimage based on the determined amount of light to be added to the scene.

In some embodiments, the image analysis module 230 determines luminancevalues (c) for the pixels in the ambient RAW image 610 a. Similarly, insome embodiments, the image analysis module 230 determines luminancevalues (x) for the pixels (in the pre-flash RAW image 620 a. Similarly,in some embodiments, the image analysis module 230 determines luminancevalues (y) for the pixels in the pre-flash JPG image 620 b. In someembodiments, the image analysis module 230 determines target luminancevalues (z) for pixels in third primary image to be captured in block418. In some embodiments, the luminance values (c), (x), and (y) aredetermined per pixel. In some embodiments, the luminance values (c),(x), and (y) are determined as the average luminance per cell of A×Bpixels (e.g., 16×16 pixels).

In some embodiments, the image analysis module 230 determines luminancevalues (c), (x), and/or (y) for pixels in areas where the pre-flash addslight (e.g., the foreground data). In some embodiments, the imageanalysis module 230 determines luminance values (c), (x), and/or (y) forpixels within the Nth (e.g., 90th) percentile of the luminosityhistogram 625. In some embodiments, the image analysis module 230determines the target luminance values (z) for pixels within the Nthpercentile (e.g., 90th) of the luminosity histogram 625 based on theluminance values (y). For example, the target luminance values (z)correspond to an M % increase (e.g., 25%) in luminance relative to theluminance values (y). For example, with reference to FIG. 6, the value630 corresponds to N, and the value 640 corresponds to M.

f(y)=x+c   (1)

f(z)=ax+c   (2)

As shown by equation (1), the luminance values (y) are a function of theluminance values (x) and (c). Similarly, as shown by equation (2), thetarget luminance values (z) are a function of the luminance values (x)and (c) and the luminance gain value (a).

f(x)=1.25(x)^(0.6)   (3)

y=1.25(x+c)^(0.6)   (4)

z=1.25(ax+c)^(0.6)   (5)

In some embodiments, the equations (4) and (5) are derived from thepredetermined function (3) for f(x). According to some embodiments, thefunction (3) for f(x) may be changed in various embodiments. In otherwords, N, M, and f(x) are tunable parameters that are set based on userinputs, machine learning, neural networks, artificial intelligence (AI),and/or the like.

The luminance gain value (a) is solved for based on the equations (4)and (5). According to some embodiments, the luminance gain value (a)corresponds to the amount of light to added to the scene for a thirdprimary image in order to balance the foreground-background luminosityas described above. In some embodiments, the luminance gain value (a) isdetermined for each of the pixels within the Nth percentile (e.g., 90th)of the luminosity histogram 625.

According to some embodiments, with reference to FIG. 2 and FIG. 6, theimage processing module 220, normalizes the ambient JPG image 610 b andthe pre-flash JPG image 620 b based on potential integration time, gaindifferences, and/or the like. Thereafter, in some embodiments, withreference to FIG. 2, the image analysis module 220 determines localstatistics (e.g., average luminance) per cell of A×B pixels (e.g., 16×16pixels) in the ambient JPG image 610 b and the pre-flash JPG image 620 baccording to a predefined algorithm (e.g., overall mean luminance percell, overall median luminance per cell, highest luminance value percell, lowest luminance value per cell, mean luminance of highest Nvalues per cell, median luminance of highest M values per cell, etc.).For example, the image processing module 220 determines a localluminance value for each cell of A×B pixels (e.g., 16×16 pixels) in theambient JPG image 610 b and the pre-flash JPG image 620 b.

In some embodiments, with reference to FIG. 2, the image analysis module220 determines macro statistics (e.g., average luminance) for theambient JPG image 610 b and the pre-flash JPG image 620 b based on theaforementioned local statistics according to a predefined algorithm(e.g., overall mean luminance across the local statistics, overallmedian luminance across the local statistics, highest luminance valueacross the local statistics, lowest luminance value across the localstatistics, mean luminance of highest N values across the localstatistics, median luminance of highest M values across the localstatistics, etc.). For example, the image processing module 220determines a macro luminance value for each of the ambient JPG image 610b and the pre-flash JPG image 620 b. For example, the image processingmodule 220 also determines a luminance delta value based on thedifference between the macro luminance values for the ambient JPG image610 b and the pre-flash JPG image 620 b. In other words, the luminancedelta value corresponds to equation (6) below.

luminance_(Δ)=macro luminance_(ambient)−macro luminance_(pre-flash)  (6)

In some embodiments, with reference to FIG. 2, the image analysis module220 determines weighted macro statistics (e.g., average luminance) forthe ambient JPG image 610 b based on the weighted difference of theaforementioned local statistics according to a predefined algorithm(e.g., overall mean luminance across the weighted local statistics,overall median luminance across the weighted local statistics, etc.),where, for example, cells with a greater relative difference between theambient local statistics and the pre-flash local statistics are weightedgreater according to a linear model, logarithmic model, or the like. Forexample, the image processing module 220 determines a weighted macroluminance value for the ambient JPG image 610 b and a macro luminancevalue for the pre-flash JPG image 620 b. For example, the imageprocessing module 220 also determines a weighted luminance delta valuebased on the difference between the weighted macro luminance value forthe ambient JPG image 610 b and the macro luminance value for thepre-flash JPG image 620 b. In other words, the weighted luminance deltavalue corresponds to equation (7) below.

weighted luminance_(Δ)=weighted macro luminance_(ambient)−macroluminance_(pre-flash)   (7)

Thereafter, the following system of equations (8) and (9) is solved todetermine one or more illuminance parameters (e.g., flash durationvalue) and/or one or more one or more image parameters (e.g., exposureperiod value), or a ratio thereof.

target_(A)=(weighted macro luminance_(ambient)*exposureperiod*gain)+(weighted luminance_(Δ)*flash duration*exposureperiod*gain)   (8)

target_(B)=(macro luminance_(ambient)*exposureperiod*gain)+(luminance_(Δ)* flash duration*exposure period*gain) (9)

According to some embodiments, the following tunable parameters are setto achieve predetermined target values A and B—the exposure periodvalue, the gain value and the flash duration value. For example, thetarget value A corresponds to the luminance associated with theforeground because it takes into account the weighted the differencebetween the luminance values of the ambient and pre-flash images.Whereas, in this example, the target value B corresponds to the overallluminance (e.g., foreground+background luminance values). In someembodiments, target values A and B are pre-determined values.

When solving the system of equations (8) and (9), the result is a ratiobetween the exposure period value and flash duration value remains. Insome embodiments, this ratio can be set between 0 and 1. According tosome embodiments, the gain value is set based on a heuristic, which usesa gain value that reduces noise (e.g., a low gain value).

The method 400 continues, at block 414, with the electronic devicedetermining one or more illumination control parameters based on theanalysis results from block 406. For example, with reference to FIG. 2,the image analysis module 230 (or the image capture control module 210)determines the one or more illumination control parameters (e.g., theflash duration, intensity, timing relative to the image exposure window,color temperature, directionality, and/or the like) for the thirdprimary image based on the image analysis data determined in block 406.In another example, with reference to FIG. 2, the image analysis module230 (or the image capture control module 210) determines the one or moreillumination control parameters (e.g., the flash duration, intensity,timing relative to the image exposure window, color temperature,directionality, and/or the like) for the third primary image based onthe determined luminance gain values (a).

The method 400 continues, at block 416, with the electronic devicedetermining one or more image parameters based on the analysis resultsfrom block 406. For example, with reference to FIG. 2, the imageanalysis module 230 (or the image capture control module 210) determinesthe one or more image parameters (e.g., the gain, exposure, shutterspeed, aperture, ISO, and/or the like) for the third primary image basedon the image analysis data determined in block 406.

As will be appreciated by one of ordinary skill in the art, although themethod 400 corresponds to determining the one or more illuminationcontrol parameters and the one or more image parameters in parallel inblocks 414 and 416, in other various embodiments, the one or moreillumination control parameters and/or the one or more image parametersare determined sequentially.

The method 400 continues, at block 418, with the electronic deviceobtaining (e.g., capturing) a third primary image of the scene inaccordance with the determined one or more illumination controlparameters from block 414 and/or the one or more image parameters fromblock 416. For example, with reference to FIG. 2, while the illuminationcomponent 130 is set to the active state in accordance with the one ormore illumination control parameters determined in block 414 and theimage capture component 120 is set in accordance with the imageparameters determined in block 416, the image capture architecture 200obtains the third primary image data (e.g., RAW image data) of the scenefrom the image sensor 122. According to some embodiments, the thirdprimary image is captured while the image capture architecture 200operates the image capture component 120 according to known AF, AE, AWB,and/or OSI algorithms or techniques in the art.

FIG. 5 is a flowchart representation of a method 500 of capturing animage with balanced foreground-background luminosity in accordance withsome embodiments. In some embodiments (and as detailed below as anexample), the method 500 is performed by an electronic device (or aportion thereof), such as the electronic device 100 in FIG. 1 or theimage capture architecture 200 in FIG. 2, that includes one or moreprocessors, non-transitory memory, an image sensor, and an illuminationcomponent. For example, the electronic device includes an image capturearchitecture with a suitable combination of an image sensor, lensassembly, shutter, aperture, and/or the like. For example, theillumination component corresponds to a flash/strobe including one ormore LEDs.

In some embodiments, the method 500 is performed by processing logic,including hardware, firmware, software, or a suitable combinationthereof. In some embodiments, the method 500 is performed by one or moreprocessors executing code, programs, or instructions stored in anon-transitory computer-readable storage medium (e.g., a non-transitorymemory). Some operations in method 500 are, optionally, combined and/orthe order of some operations is, optionally, changed. Briefly, themethod 500 includes: determining a foreground estimation based onanalysis of a first ambient image and a second pre-flash image; anddetermining illumination control parameters and/or image parametersbased on the foreground estimation in order to capture an image withbalanced foreground-background luminosity.

The method 500 begins, at block 502, with the electronic deviceobtaining (e.g., capturing) a first ambient image of a scene. Accordingto some embodiments, the operations and/or functions of block 502 aresimilar to and adapted from the operations and/or functions of block 402in FIG. 4. As such, they will not be discussed again for the sake ofbrevity.

The method 500 continues, at block 504, with the electronic deviceobtaining (e.g., capturing) a second pre-flash image of the scene.According to some embodiments, the operations and/or functions of block504 are similar to and adapted from the operations and/or functions ofblock 404 in FIG. 4. As such, they will not be discussed again for thesake of brevity.

According to some embodiments, the first ambient image is captured priorto the second pre-flash image. In some embodiments, when the firstambient image is captured prior to the second pre-flash image, one ormore subsequent ambient images are captured to provide further iterativedata points for the difference function at block 506. According to someembodiments, the first ambient image is captured after the secondpre-flash image. In some embodiments, the first ambient image and thesecond pre-flash image are captured within a predefined time period ofone another (e.g., within 100 μs, 1 ms, 10 ms, etc.).

The method 500 continues, at block 506, with the electronic deviceperforming a difference function between the first and second images toobtain a foreground estimation. For example, with reference to FIG. 2,the image processing module 220 pre-processes the first image data andthe second image data. Continuing with this example, with reference toFIG. 2, the image analysis module 230 performs image analysis on thepre-processed first image data and second image data (or acomparison/function thereof) to obtain image analysis data (e.g., theanalysis results). In some embodiments, the image analysis module 230performs a difference function between the first and second image datato generate a foreground estimation of the scene.

For example, the foreground estimation is used to discriminateforeground data from background data within the scene in order tosatisfy a foreground-background luminosity criterion that balances theforeground-background luminosity. In some embodiments, the foregroundestimation corresponds to a difference mask between the first and secondimages based on relative brightness differences of the constituentpixels. For example, with reference to FIG. 2, the image analysis module230 subtracts the luminance values of pixels in the second image fromthe luminance values of pixels in the first image to isolate theforeground and to obtain the foreground estimation. In another example,with reference to FIG. 2, the image analysis module 230 subtracts theluminance values of each cell of A×B pixels in the second image from theluminance values of each cell of A×B pixels in the first image toisolate the foreground and to obtain the foreground estimation.

As such, the comparison/function between the first and second imagescorresponds to the difference equation. In some embodiments, thecomparison/function between the first and second images corresponds to aluminance difference. In some embodiments, the comparison/functionbetween the first and second images corresponds to a relative differencewith respect to brightness. In some embodiments, the comparison/functionbetween the first and second images corresponds to a soft decision.

In some embodiments, the first and second images correspond to RAW imagedata that are converted to pre-processed (e.g., JPG) image data. In someembodiments, prior to performing the difference function between thefirst and second images, the electronic device or an element thereof(e.g., the image processing module 220 or the image analysis module 230in FIG. 2): removes clipped regions between the first and second images,blurs the first and second images, and aligns the first and secondimages. In some embodiments, after performing the difference functionbetween the first and second images, the electronic device or an elementthereof (e.g., the image processing module 220 or the image analysismodule 230 in FIG. 2) removes clipped regions in the foregroundestimation and blurs the foreground estimation.

In some embodiments, the foreground estimation corresponds to a localaverage for each cell in a grid of A×B pixel cells (e.g., 16×16 pixelcells) when performing the difference equation. This helps to reduce theeffects of misalignment of the first and second images resulting fromdevice/camera shake. In some embodiments, the electronic device or anelement thereof (e.g., the image processing module 220 or the imageanalysis module 230 in FIG. 2) generates a luminosity histogram based onthe difference between the first and second images in order to determinehow much light was added by the pre-flash.

As one example, in FIG. 7, the image 702 shows an unprocessed foregroundestimation between the first ambient image and the second pre-flashimage. In this example, the foreground subject has been isolated butbackground noise associated with ambient light sources remains.

In some embodiments, with reference to block 508, the electronic devicenormalizes the first and second images. In some embodiments, prior togenerating the foreground estimation, the electronic device or anelement thereof (e.g., the image processing module 220 or the imageanalysis module 230 in FIG. 2) normalizes the first and second imagesbased on the settings of the image capture component 120 such as shutterspeed, aperture, ISO, and/or the like. In some embodiments, the firstand second images are normalized before performing the differencefunction between the two images. For example, with reference to FIG. 2,the image analysis module 230 normalizes the first and second imagesbased on the image parameters and/or settings of the image capturecomponent 120 at the time of capturing the first and second images.

In some embodiments, with reference to block 510, the electronic devicealigns the first and second images. In some embodiments, alignment ofthe background is important in order to generate an accurate foregroundestimation. In some embodiments, the first and second images are alignedbefore performing the difference function between the two images. Forexample, with reference to FIG. 2, the image analysis module 230 alignsthe first and second images according to known algorithms or techniques(e.g., an alignment technique similar to that for aligning frames of apanorama image).

In some embodiments, with reference to block 512, the electronic deviceblurs the foreground estimation. In some embodiments, the first andsecond images are blurred based on a predefined blurring scheme ortechnique before performing the difference function between the twoimages. In some embodiments, the blurring is performed to reduce errorsfrom device/camera shake. For example, with reference to FIG. 2, theimage analysis module 230 blurs the foreground estimation according toknown algorithms or techniques. In some embodiments, the blurring isperformed based on the predefined blurring scheme or technique afterperforming the difference function between the first and second images.

As one example, in FIG. 7, the image 704 shows a blurred foregroundestimation between the first ambient image and the second pre-flashimage. In this example, the foreground subject has been further isolatedbut spurious background noise associated with the ambient light sourcesstill remains.

In some embodiments, with reference to block 514, the electronic deviceremoves clipped regions from the foreground estimation. In someembodiments, in order to reduce errors from misalignment due todevice/camera shake, a portion of the first image that is not also inthe second image (or vice versa) is removed from the foregroundestimation. In some embodiments, the clipped regions are removed beforeperforming the difference function between the first and second images.For example, with reference to FIG. 2, the image analysis module 230identifies clipped regions between the first and second regions andremoves the clipped regions from the foreground estimation. In someembodiments, the clipped regions are removed after performing thedifference function between the first and second images.

For example, misaligned light sources may introduce false positives whenisolating foreground data. As such, the electronic device or an elementthereof (e.g., the image processing module 220 or the image analysismodule 230 in FIG. 2) isolates the clipped/misaligned regions andobtains a map of those regions that are clipped in both images. In someembodiments, the contrast of the clipped regions is stretched andbinarized by applying a sigmoid. In some embodiments, the first andsecond images are multiplied so that only the regions that are clippedin both remain. In some embodiments, the regions are dilated to haveextra margins and then removed from the foreground estimation.

As one example, in FIG. 7, the image 706 shows clipped regions betweenthe first ambient image and the second pre-flash image. As one example,in FIG. 7, the image 708 shows a blurred foreground estimation between afirst ambient image and a second pre-flash image with the clippedregions from the image 706 removed. In this example, the foregroundsubject has been further isolated and the background noise associatedwith the ambient light sources is further reduced.

In some embodiments, with reference to block 516, the electronic deviceincreases the weight associated with a selected focus region within theforeground estimation. For example, the electronic device or an elementthereof (e.g., the one or more I/O devices 110 in FIGS. 1-2) detects aninput (e.g., a tap-to-focus gesture on the touch screen display) thatcorresponds to selecting a focus area within the image preview, and theselected focus area is weighted as the foreground data. For example,with reference to FIG. 2, the image analysis module 230 obtains anindication of a selected focus region and weights the pixels associatedwith the selected focus region greater than other pixels when performingthe image analysis.

In some embodiments, with reference to block 518, the electronic deviceincreases the weight associated with one or more detected faces withinthe foreground estimation. For example, the electronic device or anelement thereof (e.g., the image processing module 220 or the imageanalysis module 230 in FIG. 2) detects one or more faces within thefirst and/or second images, and the detected faces are weighted as theforeground data. In some embodiments, if two or more faces are detected,electronic device or an element thereof (e.g., the image processingmodule 220 or the image analysis module 230 in FIG. 2) gives the largestface (e.g., in pixel area) the most weight (e.g., this assumes that thelargest face is closest to the electronic device). For example, withreference to FIG. 2, the image analysis module 230 obtains an indicationof one or more detected faces (e.g., from the image analysis module 220)and weights the pixels associated with the detected faces greater thanother pixels when performing the image analysis.

In some embodiments, the electronic device performs the operationscorresponding to blocks 512, 514, 516, and 518 sequentially according tothe order shown in FIG. 5. In some embodiments, the electronic deviceperforms the operations corresponding to blocks 512, 514, 516, and 518sequentially according to an order different from the order shown inFIG. 5. In some embodiments, the electronic device performs theoperations corresponding to blocks 512, 514, 516, and 518 in parallel.

The method 500 continues, at block 520, with the electronic deviceprocessing and analyzing the foreground estimation from block 506. Insome embodiments, the image analysis module 230 processes and analyzesthe foreground estimation generated in block 506. In some embodiments,the image analysis module 230 generates a delta luminosity histogrambased on the foreground estimation. In some embodiments, the imageanalysis module 230 (or the image capture control module 210) determinesone or more illumination control parameters for the third primary imagebased on the delta luminosity histogram. In some embodiments, the imageanalysis module 230 (or the image capture control module 210) determinesone or more illumination control parameters and/or one or more imageparameters based on the image analysis data (e.g., the analysisresults).

In some embodiments, with reference to block 522, the electronic devicegenerates a delta luminosity histogram based on the foregroundestimation from block 506. According to some embodiments, the imageanalysis module 230 generates the delta luminosity histogram based onthe luminance values of the pixels in the foreground estimation (e.g., aforeground mask generated by performing the difference function betweenthe first and second images in block 506).

For example, the image analysis module 230 generates the deltaluminosity histogram for the foreground estimation similar to theluminosity histogram 625 described above with reference to block 406. Insome embodiments, the image analysis module 230 determines: luminancevalues (y) for the pixels in the foreground estimation, luminance values(c) for the pixels in the first ambient image, and luminance values (x)for the pixels in the second pre-flash image. In some embodiments, theimage analysis module 230 determines the luminance values (c), (x),and/or (y) for pixels within the Nth (e.g., 90th) percentile of thedelta luminosity histogram. In some embodiments, the image analysismodule 230 determines the target luminance values (z) for pixels withinthe Nth percentile (e.g., 90th) of the delta luminosity histogram basedon the luminance values (y). For example, the target luminance values(z) correspond to an M % increase (e.g., 25%) in luminance relative tothe luminance values (y).

As shown by equation (1) above, the luminance values (y) are a functionof the luminance values (x) and (c). Similarly, as shown by equation (2)above, the target luminance values (z) are a function of the luminancevalues (x) and (c) and the luminance gain value (a). The luminance gainvalue (a) is solved for based on the equations (4) and (5) above.According to some embodiments, the luminance gain value (a) correspondsto the amount of light to added to the scene for a third primary imagein order to balance the foreground-background. In some embodiments, theluminance gain value (a) is determined for each of the pixels within theNth percentile (e.g., 90th) of the delta luminosity histogram.

The method 500 continues, at block 524, with the electronic devicedetermining one or more illumination control parameters and/or one ormore image parameters based on the analysis results from block 520. Forexample, the illumination control parameters correspond to the flashtiming relative to the image exposure window such as rear-curtainsynchronization, the flash duration, the flash intensity, the colortemperature of flash LEDs, the directionality of flash LEDs, and/or thelike. For example, the image parameters correspond to gain, exposure,shutter speed, aperture, ISO, and/or the like.

For example, if the delta luminosity histogram generated in block 522indicates that the foreground is close to the electronic device, theflash duration is short. In another example, if delta luminosityhistogram generated in block 522 indicates that the foreground isfarther from the electronic device, the flash duration is longer. Insome embodiments, the one or more illumination control parameters areselected such that a luminosity histogram of the third primary imagewould be stretched relative to the delta luminosity histogram such thatthe third primary image has a more Gaussian luminous distribution.

For example, with reference to FIG. 2, the image analysis module 230 (orthe image capture control module 210) determines the one or moreillumination control parameters (e.g., the flash duration, intensity,timing relative to the image exposure window, color temperature,directionality, and/or the like) for the third primary image based onthe image analysis data determined in block 520. In another example,with reference to FIG. 2, the image analysis module 230 (or the imagecapture control module 210) determines the one or more illuminationcontrol parameters (e.g., the flash duration, intensity, timing relativeto the image exposure window, color temperature, directionality, and/orthe like) for the third primary image based on the determined luminancegain values (a) from the delta luminosity histogram. For example, withreference to FIG. 2, the image analysis module 230 (or the image capturecontrol module 210) determines the one or more image parameters (e.g.,the gain, exposure, shutter speed, aperture, ISO, and/or the like) forthe third primary image based on the image analysis data determined inblock 520.

As will be appreciated by one of ordinary skill in the art, although themethod 500 corresponds to concurrently determining the one or moreillumination control parameters and/or the one or more image parametersin block 524, in other various embodiments, the one or more illuminationcontrol parameters and/or the one or more image parameters aredetermined sequentially.

The method 500 continues, at block 526, with the electronic deviceobtaining (e.g., capturing) a third primary image of the scene inaccordance with the determined one or more illumination controlparameters from block 524 and/or the one or more image parameters fromblock 524. For example, with reference to FIG. 2, while the illuminationcomponent 130 is set to the active state in accordance with the one ormore illumination control parameters determined in block 524 and theimage capture component 120 is set in accordance with the imageparameters determined in block 524, the image capture architecture 200obtains the third primary image data (e.g., RAW image data) of the scenefrom the image sensor 122. According to some embodiments, the thirdprimary image is captured while the image capture architecture 200operates the image capture component 120 according to known AF, AE, AWB,and/or OSI algorithms or techniques in the art.

With reference to FIG. 8, the first image capture scenario 800illustrates a first flash period 820 starting at time 822 and ending attime 824 and a first image exposure window 830 (e.g., 62 ms) starting attime 812 and ending at time 814. As shown in FIG. 8, the first imagecapture scenario 800 includes a front-curtain flash because the time 822(e.g., the start of the first flash period 820) occurs before the time812 (e.g., the start of the first image exposure period 830). As shownin FIG. 8, the first image capture scenario 800 also includes arear-curtain because the time 824 (e.g., the end of the first flashperiod 820) occurs after the time 814 (e.g., the end of the first imageexposure period 830). According to some embodiments, the electronicdevice or an element thereof (e.g., the image capture component 120 inFIGS. 1-2) captures the third primary image according to the imageexposure window, flash timing relative to the image capture window, andthe flash period duration in the first image capture scenario 800 whenblocks 502-524 are not performed.

With continued reference to FIG. 8, the second image capture scenario850 illustrates a second flash period 820′ starting at time 822′ andending at time 824′ and a second image exposure window 830′ (e.g., 250ms) starting at time 812′ and ending at time 814′. As shown in FIG. 8,in the second image capture scenario 850, the second flash period 820′is synchronized to the end of the second image exposure window 830′.According to some embodiments, this enables a motion freeze effect aswell as a motion trail for moving objects in the third primary image.

In some embodiments, the electronic device or an element thereof (e.g.,the image analysis module 230 or the image capture control module 210 inFIG. 2) synchronizes the flash period to the end of the image exposurecapture window as shown in the second image capture scenario 850. Insome embodiments, the image exposure capture window is a predefined(e.g., static) time duration. In some embodiments, the electronic deviceor an element thereof (e.g., the image analysis module 230 or the imagecapture control module 210 in FIG. 2) dynamically determines the imageexposure capture window based on the determined image parameters inblock 524. According to some embodiments, the electronic device or anelement thereof (e.g., the image capture component 120 in FIGS. 1-2)captures the third primary image according to the image exposure window,flash timing relative to the image capture window, and the flash periodduration in the second image capture scenario 850 based on thedetermined one or more illumination control parameters and/or imageparameters from block 524.

FIG. 9 is a block diagram of a computing device 900 in accordance withsome embodiments. In some embodiments, the computing device 900corresponds to the at least a portion of the electronic device 100 inFIG. 1 and performs one or more of the functionalities described abovewith respect to the electronic device. While certain specific featuresare illustrated, those skilled in the art will appreciate from thepresent disclosure that various other features have not been illustratedfor the sake of brevity, and so as not to obscure more pertinent aspectsof the embodiments disclosed herein. To that end, as a non-limitingexample, in some embodiments the computing device 900 includes one ormore processing units (CPUs) 902 (e.g., processors), one or moreinput/output (I/O) interfaces 903 (e.g., network interfaces, inputdevices, output devices, and/or sensor interfaces), a memory 910, aprogramming interface 905, and one or more communication buses 904 forinterconnecting these and various other components.

In some embodiments, the communication buses 904 include circuitry thatinterconnects and controls communications between system components. Thememory 910 includes high-speed random-access memory, such as DRAM, SRAM,DDR RAM or other random-access solid-state memory devices; and, in someembodiments, include non-volatile memory, such as one or more magneticdisk storage devices, optical disk storage devices, flash memorydevices, or other non-volatile solid state storage devices. The memory910 optionally includes one or more storage devices remotely locatedfrom the CPU(s) 902. The memory 910 comprises a non-transitory computerreadable storage medium. Moreover, in some embodiments, the memory 910or the non-transitory computer readable storage medium of the memory 910stores the following programs, modules and data structures, or a subsetthereof including an optional operating system 920, an image capturecontrol module 950, an image processing module 952, and an imageanalysis module 954. In some embodiments, one or more instructions areincluded in a combination of logic and non-transitory memory. Theoperating system 920 includes procedures for handling various basicsystem services and for performing hardware dependent tasks.

In some embodiments, the image capture control module 950 is configuredto control the functionality of a camera (e.g., the image capturecomponent 120 in FIGS. 1-2) and a flash/strobe (e.g., the illuminationcomponent 130 in FIGS. 1-2). To that end, the image capture controlmodule 950 includes a set of instructions 951 a and heuristics andmetadata 951 b.

In some embodiments, the image processing module 952 is configured topre-process raw image data from an image sensor (e.g., the image sensor122 in FIGS. 1-2). To that end, the image processing module 952 includesa set of instructions 953 a and heuristics and metadata 953 b.

In some embodiments, the image analysis module 954 is configured toperform analysis on the image data. In some embodiments, the imageanalysis module 954 is also configured to determine one or more imageparameters and/or one or more illumination control parameters based onthe image analysis results. To that end, the image analysis module 954includes a set of instructions 955 a and heuristics and metadata 955 b.

Although the image capture control module 950, the image processingmodule 952, and the image analysis module 954 are illustrated asresiding on a single computing device 900, it should be understood thatin other embodiments, any combination of the image capture controlmodule 950, the image processing module 952, and the image analysismodule 954 can reside in separate computing devices in variousembodiments. For example, in some embodiments each of the image capturecontrol module 950, the image processing module 952, and the imageanalysis module 954 reside on a separate computing device or in thecloud.

Moreover, FIG. 9 is intended more as a functional description of thevarious features which are present in a particular implementation asopposed to a structural schematic of the embodiments described herein.As recognized by those of ordinary skill in the art, items shownseparately could be combined and some items could be separated. Forexample, some functional modules shown separately in FIG. 9 could beimplemented in a single module and the various functions of singlefunctional blocks could be implemented by one or more functional blocksin various embodiments. The actual number of modules and the division ofparticular functions and how features are allocated among them will varyfrom one embodiment to another, and may depend in part on the particularcombination of hardware, software and/or firmware chosen for aparticular embodiment.

The present disclosure describes various features, no single one ofwhich is solely responsible for the benefits described herein. It willbe understood that various features described herein may be combined,modified, or omitted, as would be apparent to one of ordinary skill.Other combinations and sub-combinations than those specificallydescribed herein will be apparent to one of ordinary skill, and areintended to form a part of this disclosure. Various methods aredescribed herein in connection with various flowchart steps and/orphases. It will be understood that in many cases, certain steps and/orphases may be combined together such that multiple steps and/or phasesshown in the flowcharts can be performed as a single step and/or phase.Also, certain steps and/or phases can be broken into additionalsub-components to be performed separately. In some instances, the orderof the steps and/or phases can be rearranged and certain steps and/orphases may be omitted entirely. Also, the methods described herein areto be understood to be open-ended, such that additional steps and/orphases to those shown and described herein can also be performed.

Some or all of the methods and tasks described herein may be performedand fully automated by a computer system. The computer system may, insome cases, include multiple distinct computers or computing devices(e.g., physical servers, workstations, storage arrays, etc.) thatcommunicate and interoperate over a network to perform the describedfunctions. Each such computing device typically includes a processor (ormultiple processors) that executes program instructions or modulesstored in a memory or other non-transitory computer-readable storagemedium or device. The various functions disclosed herein may be embodiedin such program instructions, although some or all of the disclosedfunctions may alternatively be implemented in application-specificcircuitry (e.g., ASICs or FPGAs or GP-GPUs) of the computer system.Where the computer system includes multiple computing devices, thesedevices may, but need not, be co-located. The results of the disclosedmethods and tasks may be persistently stored by transforming physicalstorage devices, such as solid state memory chips and/or magnetic disks,into a different state.

The disclosure is not intended to be limited to the embodiments shownherein. Various modifications to the embodiments described in thisdisclosure may be readily apparent to those skilled in the art, and thegeneric principles defined herein may be applied to other embodimentswithout departing from the spirit or scope of this disclosure. Theteachings of the invention provided herein can be applied to othermethods and systems, and are not limited to the methods and systemsdescribed above, and elements and acts of the various embodimentsdescribed above can be combined to provide further embodiments.Accordingly, the novel methods and systems described herein may beembodied in a variety of other forms; furthermore, various omissions,substitutions and changes in the form of the methods and systemsdescribed herein may be made without departing from the spirit of thedisclosure. The accompanying claims and their equivalents are intendedto cover such forms or modifications as would fall within the scope andspirit of the disclosure.

What is claimed is:
 1. A method comprising: at a device with one or moreprocessors, non-transitory memory, an image sensor, and an illuminationcomponent: obtaining, by the image sensor, a first image of a scenewhile the illumination component is set to an inactive state; obtaining,by the image sensor, a second image of the scene while the illuminationcomponent is set to a pre-flash state; determining one or moreillumination control parameters for the illumination component for athird image of the scene that satisfy a foreground-background balancecriterion based on a function of the first and second images in order todiscriminate foreground data from background data within the scene; andobtaining, by the image sensor, the third image of the scene while theillumination component is set to an active state in accordance with theone or more illumination control parameters.
 2. The method of claim 1,wherein the one or more illumination control parameters set a flashperiod of the illumination component for the third image relative to apredefined exposure period of the third image.
 3. The method of claim 1,further comprising, determining one or more image parameters for theimage sensor for the third image based on a function of the first andsecond images in order to discriminate the foreground data from thebackground data within the scene, wherein one of the one or more imageparameters sets an exposure period for the third image, and wherein theone or more illumination control parameters set a flash period of theillumination component for the third image relative to the exposureperiod of the third image.
 4. The method of claim 1, wherein the one ormore illumination control parameters correspond to one of a flash timingparameter relative to an exposure of the third image, a flash durationparameter, a flash intensity parameter, a flash color temperatureparameter, or a flash directionality parameter.
 5. The method of claim1, further comprising, generating a foreground estimation of the scenebased at least in part on a comparison of the first and second images,wherein the one or more illumination control parameters are determinedbased on the foreground estimation.
 6. The method of claim 5, whereingenerating the foreground estimation includes performing a differencefunction between the first and second images in order to generate theforeground estimation, and the method further comprising: generating adelta luminosity histogram based on the foreground estimation, whereinthe foreground estimation is provided by the difference function betweenthe first and second images.
 7. The method claim 6, wherein determiningthe one or more illumination control parameters for the illuminationcomponent for the third image includes: determining the one or moreillumination control parameters for the illumination component for thethird image such that the third image satisfies an illuminationcriterion, wherein the third image satisfies the illumination criterionwhen a luminosity histogram of the third image indicates greaterilluminance distribution compared to the delta luminosity histogram. 8.The method of claim 5, wherein generating the foreground estimationincludes normalizing the first image and the second image based oncamera settings.
 9. The method of claim 5, wherein generating theforeground estimation includes aligning the first and second images. 10.The method of claim 5, wherein generating the foreground estimationincludes removing a clipped portion that corresponds to the first imageand not the second image.
 11. The method of claim 5, wherein generatingthe foreground estimation includes blurring the first and second imagesaccording to predefined blur criteria.
 12. The method of claim 5,wherein generating the foreground estimation of the scene includesgenerating the foreground estimation of the scene based at least in parton a selected focus area and the comparison of the second image and thefirst image.
 13. An electronic device comprising: an image sensor; anillumination component; a non-transitory memory; one or more processors;and one or more programs, wherein the one or more programs are stored inthe non-transitory memory and configured to be executed by the one ormore processors, the one or more programs including instructions for:obtaining, by the image sensor, a first image of a scene while theillumination component is set to an inactive state; obtaining, by theimage sensor, a second image of the scene while the illuminationcomponent is set to a pre-flash state; determining one or moreillumination control parameters for the illumination component for athird image of the scene that satisfy a foreground-background balancecriterion based on a function of the first and second images in order todiscriminate foreground data from background data within the scene; andobtaining, by the image sensor, the third image of the scene while theillumination component is set to an active state in accordance with theone or more illumination control parameters.
 14. The electronic deviceof claim 13, wherein the one or more illumination control parameters seta flash period of the illumination component for the third imagerelative to a predefined exposure period of the third image.
 15. Theelectronic device of claim 13, wherein the one or more programs includeinstructions for determining one or more image parameters for the imagesensor for the third image based on a function of the first and secondimages in order to discriminate the foreground data from the backgrounddata within the scene, wherein one of the one or more image parameterssets an exposure period for the third image, and wherein the one or moreillumination control parameters set a flash period of the illuminationcomponent for the third image relative to the exposure period of thethird image.
 16. The electronic device of claim 13, wherein the one ormore illumination control parameters correspond to one of a flash timingparameter relative to an exposure of the third image, a flash durationparameter, a flash intensity parameter, a flash color temperatureparameter, or a flash directionality parameter.
 17. The electronicdevice of claim 13, wherein the one or more programs includeinstructions for generating a foreground estimation of the scene basedat least in part on a comparison of the first and second images, whereinthe one or more illumination control parameters are determined based onthe foreground estimation.
 18. The electronic device of claim 17,wherein generating the foreground estimation includes performing adifference function between the first and second images in order togenerate the foreground estimation, and wherein the one or more programsinclude instructions for: generating a delta luminosity histogram basedon the foreground estimation, wherein the foreground estimation isprovided by the difference function between the first and second images.19. The electronic device claim 18, wherein determining the one or moreillumination control parameters for the illumination component for thethird image includes: determining the one or more illumination controlparameters for the illumination component for the third image such thatthe third image satisfies an illumination criterion, wherein the thirdimage satisfies the illumination criterion when a luminosity histogramof the third image indicates greater illuminance distribution comparedto the delta luminosity histogram.
 20. A non-transitory computerreadable storage medium storing one or more programs, the one or moreprograms comprising instructions, which, when executed by one or moreprocessors of an electronic device with an image sensor and anillumination component, cause the electronic device to: obtain, by theimage sensor, a first image of a scene while the illumination componentis set to an inactive state; obtain, by the image sensor, a second imageof the scene while the illumination component is set to a pre-flashstate; determine one or more illumination control parameters for theillumination component for a third image of the scene that satisfy aforeground-background balance criterion based on a function of the firstand second images in order to discriminate foreground data frombackground data within the scene; and obtain, by the image sensor, thethird image of the scene while the illumination component is set to anactive state in accordance with the one or more illumination controlparameters.